Deepfake Detection in the Era of Artificial Intelligence: A Practice of Crime Prevention Strategies

Deepfake Detection in the Era of Artificial Intelligence: A Practice of Crime Prevention Strategies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Deepfake Detection in the Era of Artificial Intelligence: A Practice of Crime Prevention Strategies Sinchul Back, Raymond Partin, Byeongoh Ahn, Bo Ra Jung This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7655074/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The purpose of this study is to demonstrate how to create deepfake contents and to identify an efficient and robust platform for detecting deepfakes. Also, this study conducts an empirical test on the application of the situational crime prevention techniques for preventing deepfake misuse. To that end, this research evaluates the current deepfake generation platforms and the newly updated deepfake detection techniques using a dataset of deepfake generated images/videos. The results of this study indicate that either increasing the effort required for criminals (e.g., setting platforms to block malicious content generation) or by increasing the risk of being caught through enhanced detection systems help deter criminals by building more difficult environment(s) to commit deepfake-related crimes. Policy implications and limitations are discussed. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7655074","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":532172988,"identity":"b0128878-e076-413c-a1a6-3c23afc9ae84","order_by":0,"name":"Sinchul Back","email":"","orcid":"","institution":"University of Scranton","correspondingAuthor":false,"prefix":"","firstName":"Sinchul","middleName":"","lastName":"Back","suffix":""},{"id":532172989,"identity":"ad64e4bd-1338-487e-984c-04d5744537c7","order_by":1,"name":"Raymond Partin","email":"","orcid":"","institution":"University of 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